Pandas Profiling Report

Dataset statistics

Number of variables	15
Number of observations	6014
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	751.8 KiB
Average record size in memory	128.0 B

Variable types

Text	1
Numeric	10
Categorical	4

Alerts

`engine` is highly overall correlated with `max_power` and 3 other fields	High correlation
`fuel` is highly overall correlated with `torque_rpm_min`	High correlation
`km_driven` is highly overall correlated with `year`	High correlation
`max_power` is highly overall correlated with `engine` and 3 other fields	High correlation
`seats` is highly overall correlated with `engine`	High correlation
`selling_price` is highly overall correlated with `max_power` and 2 other fields	High correlation
`torque_Nm` is highly overall correlated with `engine` and 2 other fields	High correlation
`torque_rpm_max` is highly overall correlated with `torque_rpm_min`	High correlation
`torque_rpm_min` is highly overall correlated with `engine` and 2 other fields	High correlation
`transmission` is highly overall correlated with `max_power`	High correlation
`year` is highly overall correlated with `km_driven` and 1 other fields	High correlation
`seller_type` is highly imbalanced (68.2%)	Imbalance
`transmission` is highly imbalanced (58.2%)	Imbalance
`torque_Nm` is highly skewed (γ1 = 73.34774168)	Skewed
`max_power` has 191 (3.2%) zeros	Zeros
`torque_Nm` has 192 (3.2%) zeros	Zeros
`torque_rpm_min` has 283 (4.7%) zeros	Zeros
`torque_rpm_max` has 276 (4.6%) zeros	Zeros

Reproduction

Analysis started	2024-11-18 09:00:19.179436
Analysis finished	2024-11-18 09:00:53.545705
Duration	34.37 seconds
Software version	ydata-profiling vv4.12.0
Download configuration	config.json

name
Text

Distinct	1924
Distinct (%)	32.0%
Missing	0
Missing (%)	0.0%
Memory size	94.0 KiB

Length

Max length	54
Median length	43
Mean length	25.166279
Min length	11

Characters and Unicode

Total characters	151350
Distinct characters	68
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	905 ?
Unique (%)	15.0%

Sample

1st row	Maruti Swift Dzire VDI
2nd row	Skoda Rapid 1.5 TDI Ambition
3rd row	Hyundai i20 Sportz Diesel
4th row	Maruti Swift VXI BSIII
5th row	Hyundai Xcent 1.2 VTVT E Plus

Value	Count	Frequency (%)
maruti	1886	6.6%
hyundai	1083	3.8%
mahindra	629	2.2%
swift	592	2.1%
tata	544	1.9%
bsiv	507	1.8%
diesel	470	1.7%
1.2	435	1.5%
vxi	425	1.5%
vdi	420	1.5%
Other values (828)	21405	75.4%

Most occurring characters

Value	Count	Frequency (%)
	22383	14.8%
a	11047	7.3%
i	10130	6.7%
t	7669	5.1%
r	6677	4.4%
o	5992	4.0%
n	5773	3.8%
e	5550	3.7%
u	4474	3.0%
S	4090	2.7%
Other values (58)	67565	44.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	151350	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	22383	14.8%
a	11047	7.3%
i	10130	6.7%
t	7669	5.1%
r	6677	4.4%
o	5992	4.0%
n	5773	3.8%
e	5550	3.7%
u	4474	3.0%
S	4090	2.7%
Other values (58)	67565	44.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	151350	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	22383	14.8%
a	11047	7.3%
i	10130	6.7%
t	7669	5.1%
r	6677	4.4%
o	5992	4.0%
n	5773	3.8%
e	5550	3.7%
u	4474	3.0%
S	4090	2.7%
Other values (58)	67565	44.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	151350	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	22383	14.8%
a	11047	7.3%
i	10130	6.7%
t	7669	5.1%
r	6677	4.4%
o	5992	4.0%
n	5773	3.8%
e	5550	3.7%
u	4474	3.0%
S	4090	2.7%
Other values (58)	67565	44.6%

year
Real number (ℝ)

High correlation

Distinct	29
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2013.4475

Minimum	1983
Maximum	2020
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	1983
5-th percentile	2006
Q1	2011
median	2014
Q3	2017
95-th percentile	2019
Maximum	2020
Range	37
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.0799204
Coefficient of variation (CV)	0.0020263357
Kurtosis	1.6891091
Mean	2013.4475
Median Absolute Deviation (MAD)	3
Skewness	-1.0198946
Sum	12108873
Variance	16.64575
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
2017	696	11.6%
2016	615	10.2%
2015	585	9.7%
2018	536	8.9%
2012	524	8.7%
2014	503	8.4%
2013	488	8.1%
2011	469	7.8%
2010	329	5.5%
2019	306	5.1%
Other values (19)	963	16.0%

Value	Count	Frequency (%)
1983	1	< 0.1%
1991	1	< 0.1%
1994	3	< 0.1%
1995	1	< 0.1%
1996	3	< 0.1%
1997	10	0.2%
1998	9	0.1%
1999	12	0.2%
2000	19	0.3%
2001	7	0.1%

Value	Count	Frequency (%)
2020	59	1.0%
2019	306	5.1%
2018	536	8.9%
2017	696	11.6%
2016	615	10.2%
2015	585	9.7%
2014	503	8.4%
2013	488	8.1%
2012	524	8.7%
2011	469	7.8%

selling_price
Real number (ℝ)

High correlation

Distinct	637
Distinct (%)	10.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	521982.03

Minimum	29999
Maximum	10000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	29999
5-th percentile	100000
Q1	250000
median	409999
Q3	640000
95-th percentile	1200000
Maximum	10000000
Range	9970001
Interquartile range (IQR)	390000

Descriptive statistics

Standard deviation	533842.62
Coefficient of variation (CV)	1.0227222
Kurtosis	52.713853
Mean	521982.03
Median Absolute Deviation (MAD)	190001
Skewness	5.6236928
Sum	3.1391999 × 10⁹
Variance	2.8498794 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
300000	188	3.1%
350000	173	2.9%
400000	147	2.4%
250000	144	2.4%
550000	142	2.4%
600000	142	2.4%
500000	138	2.3%
450000	137	2.3%
200000	133	2.2%
650000	125	2.1%
Other values (627)	4545	75.6%

Value	Count	Frequency (%)
29999	1	< 0.1%
30000	2	< 0.1%
31504	1	< 0.1%
35000	3	< 0.1%
39000	1	< 0.1%
40000	12	0.2%
42000	2	< 0.1%
45000	16	0.3%
45957	1	< 0.1%
50000	15	0.2%

Value	Count	Frequency (%)
10000000	1	< 0.1%
7200000	1	< 0.1%
6523000	1	< 0.1%
6223000	1	< 0.1%
6000000	3	< 0.1%
5923000	1	< 0.1%
5850000	1	< 0.1%
5830000	1	< 0.1%
5800000	2	< 0.1%
5500000	3	< 0.1%

km_driven
Real number (ℝ)

High correlation

Distinct	827
Distinct (%)	13.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	73764.15

Minimum	1
Maximum	2360457
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	1
5-th percentile	11325
Q1	39000
median	70000
Q3	100000
95-th percentile	155000
Maximum	2360457
Range	2360456
Interquartile range (IQR)	61000

Descriptive statistics

Standard deviation	59610.747
Coefficient of variation (CV)	0.80812627
Kurtosis	416.83816
Mean	73764.15
Median Absolute Deviation (MAD)	30000
Skewness	12.58954
Sum	4.436176 × 10⁸
Variance	3.5534411 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
120000	446	7.4%
70000	373	6.2%
80000	371	6.2%
60000	342	5.7%
50000	313	5.2%
100000	290	4.8%
90000	280	4.7%
40000	238	4.0%
110000	229	3.8%
30000	192	3.2%
Other values (817)	2940	48.9%

Value	Count	Frequency (%)
1	1	< 0.1%
1000	5	0.1%
1300	1	< 0.1%
1303	1	< 0.1%
1500	2	< 0.1%
1600	1	< 0.1%
1620	1	< 0.1%
2000	6	0.1%
2118	1	< 0.1%
2136	1	< 0.1%

Value	Count	Frequency (%)
2360457	1	< 0.1%
1500000	1	< 0.1%
577414	1	< 0.1%
500000	2	< 0.1%
475000	1	< 0.1%
440000	1	< 0.1%
426000	1	< 0.1%
380000	1	< 0.1%
376412	1	< 0.1%
370000	1	< 0.1%

fuel
Categorical

High correlation

Distinct	4
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	94.0 KiB

Diesel	3269
Petrol	2660
CNG	51
LPG	34

Length

Max length	6
Median length	6
Mean length	5.9575989
Min length	3

Characters and Unicode

Total characters	35829
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Diesel
2nd row	Diesel
3rd row	Diesel
4th row	Petrol
5th row	Petrol

Common Values

Value	Count	Frequency (%)
Diesel	3269	54.4%
Petrol	2660	44.2%
CNG	51	0.8%
LPG	34	0.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
diesel	3269	54.4%
petrol	2660	44.2%
cng	51	0.8%
lpg	34	0.6%

Most occurring characters

Value	Count	Frequency (%)
e	9198	25.7%
l	5929	16.5%
D	3269	9.1%
i	3269	9.1%
s	3269	9.1%
P	2694	7.5%
t	2660	7.4%
r	2660	7.4%
o	2660	7.4%
G	85	0.2%
Other values (3)	136	0.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	35829	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	9198	25.7%
l	5929	16.5%
D	3269	9.1%
i	3269	9.1%
s	3269	9.1%
P	2694	7.5%
t	2660	7.4%
r	2660	7.4%
o	2660	7.4%
G	85	0.2%
Other values (3)	136	0.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	35829	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	9198	25.7%
l	5929	16.5%
D	3269	9.1%
i	3269	9.1%
s	3269	9.1%
P	2694	7.5%
t	2660	7.4%
r	2660	7.4%
o	2660	7.4%
G	85	0.2%
Other values (3)	136	0.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	35829	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	9198	25.7%
l	5929	16.5%
D	3269	9.1%
i	3269	9.1%
s	3269	9.1%
P	2694	7.5%
t	2660	7.4%
r	2660	7.4%
o	2660	7.4%
G	85	0.2%
Other values (3)	136	0.4%

seller_type
Categorical

Imbalance

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	94.0 KiB

Individual	5394
Dealer	595
Trustmark Dealer	25

Length

Max length	16
Median length	10
Mean length	9.6291985
Min length	6

Characters and Unicode

Total characters	57910
Distinct characters	17
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Individual
2nd row	Individual
3rd row	Individual
4th row	Individual
5th row	Individual

Common Values

Value	Count	Frequency (%)
Individual	5394	89.7%
Dealer	595	9.9%
Trustmark Dealer	25	0.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
individual	5394	89.3%
dealer	620	10.3%
trustmark	25	0.4%

Most occurring characters

Value	Count	Frequency (%)
d	10788	18.6%
i	10788	18.6%
a	6039	10.4%
l	6014	10.4%
u	5419	9.4%
I	5394	9.3%
v	5394	9.3%
n	5394	9.3%
e	1240	2.1%
r	670	1.2%
Other values (7)	770	1.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	57910	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
d	10788	18.6%
i	10788	18.6%
a	6039	10.4%
l	6014	10.4%
u	5419	9.4%
I	5394	9.3%
v	5394	9.3%
n	5394	9.3%
e	1240	2.1%
r	670	1.2%
Other values (7)	770	1.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	57910	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
d	10788	18.6%
i	10788	18.6%
a	6039	10.4%
l	6014	10.4%
u	5419	9.4%
I	5394	9.3%
v	5394	9.3%
n	5394	9.3%
e	1240	2.1%
r	670	1.2%
Other values (7)	770	1.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	57910	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
d	10788	18.6%
i	10788	18.6%
a	6039	10.4%
l	6014	10.4%
u	5419	9.4%
I	5394	9.3%
v	5394	9.3%
n	5394	9.3%
e	1240	2.1%
r	670	1.2%
Other values (7)	770	1.3%

transmission
Categorical

High correlation Imbalance

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	94.0 KiB

Manual	5505
Automatic	509

Length

Max length	9
Median length	6
Mean length	6.2539075
Min length	6

Characters and Unicode

Total characters	37611
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Manual
2nd row	Manual
3rd row	Manual
4th row	Manual
5th row	Manual

Common Values

Value	Count	Frequency (%)
Manual	5505	91.5%
Automatic	509	8.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
manual	5505	91.5%
automatic	509	8.5%

Most occurring characters

Value	Count	Frequency (%)
a	11519	30.6%
u	6014	16.0%
M	5505	14.6%
n	5505	14.6%
l	5505	14.6%
t	1018	2.7%
A	509	1.4%
o	509	1.4%
m	509	1.4%
i	509	1.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	37611	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	11519	30.6%
u	6014	16.0%
M	5505	14.6%
n	5505	14.6%
l	5505	14.6%
t	1018	2.7%
A	509	1.4%
o	509	1.4%
m	509	1.4%
i	509	1.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	37611	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	11519	30.6%
u	6014	16.0%
M	5505	14.6%
n	5505	14.6%
l	5505	14.6%
t	1018	2.7%
A	509	1.4%
o	509	1.4%
m	509	1.4%
i	509	1.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	37611	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	11519	30.6%
u	6014	16.0%
M	5505	14.6%
n	5505	14.6%
l	5505	14.6%
t	1018	2.7%
A	509	1.4%
o	509	1.4%
m	509	1.4%
i	509	1.4%

owner
Categorical

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	94.0 KiB

First Owner	3721
Second Owner	1691
Third Owner	457
Fourth & Above Owner	141
Test Drive Car	4

Length

Max length	20
Median length	11
Mean length	11.49418
Min length	11

Characters and Unicode

Total characters	69126
Distinct characters	24
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	First Owner
2nd row	Second Owner
3rd row	First Owner
4th row	First Owner
5th row	First Owner

Common Values

Value	Count	Frequency (%)
First Owner	3721	61.9%
Second Owner	1691	28.1%
Third Owner	457	7.6%
Fourth & Above Owner	141	2.3%
Test Drive Car	4	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
owner	6010	48.8%
first	3721	30.2%
second	1691	13.7%
third	457	3.7%
fourth	141	1.1%
	141	1.1%
above	141	1.1%
test	4	< 0.1%
drive	4	< 0.1%
car	4	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
r	10337	15.0%
e	7850	11.4%
n	7701	11.1%
	6300	9.1%
O	6010	8.7%
w	6010	8.7%
i	4182	6.0%
t	3866	5.6%
F	3862	5.6%
s	3725	5.4%
Other values (14)	9283	13.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	69126	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
r	10337	15.0%
e	7850	11.4%
n	7701	11.1%
	6300	9.1%
O	6010	8.7%
w	6010	8.7%
i	4182	6.0%
t	3866	5.6%
F	3862	5.6%
s	3725	5.4%
Other values (14)	9283	13.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	69126	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
r	10337	15.0%
e	7850	11.4%
n	7701	11.1%
	6300	9.1%
O	6010	8.7%
w	6010	8.7%
i	4182	6.0%
t	3866	5.6%
F	3862	5.6%
s	3725	5.4%
Other values (14)	9283	13.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	69126	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
r	10337	15.0%
e	7850	11.4%
n	7701	11.1%
	6300	9.1%
O	6010	8.7%
w	6010	8.7%
i	4182	6.0%
t	3866	5.6%
F	3862	5.6%
s	3725	5.4%
Other values (14)	9283	13.4%

mileage
Real number (ℝ)

Distinct	379
Distinct (%)	6.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	19.461072

Minimum	0
Maximum	42
Zeros	14
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	0
5-th percentile	12.9585
Q1	17
median	19.326154
Q3	22.32
95-th percentile	25.83
Maximum	42
Range	42
Interquartile range (IQR)	5.32

Descriptive statistics

Standard deviation	3.9887158
Coefficient of variation (CV)	0.20495869
Kurtosis	0.82003735
Mean	19.461072
Median Absolute Deviation (MAD)	2.6738462
Skewness	-0.16888122
Sum	117038.89
Variance	15.909854
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
18.9	184	3.1%
19.32615385	156	2.6%
19.7	146	2.4%
18.6	130	2.2%
21.1	124	2.1%
17	108	1.8%
15.96	98	1.6%
17.8	90	1.5%
16.1	86	1.4%
15.1	79	1.3%
Other values (369)	4813	80.0%

Value	Count	Frequency (%)
0	14	0.2%
9	4	0.1%
9.5	1	< 0.1%
10	2	< 0.1%
10.1	2	< 0.1%
10.5	14	0.2%
10.71	1	< 0.1%
10.75	1	< 0.1%
10.8	1	< 0.1%
10.9	4	0.1%

Value	Count	Frequency (%)
42	1	< 0.1%
33.44	2	< 0.1%
33	1	< 0.1%
32.52	1	< 0.1%
30.46	2	< 0.1%
28.4	74	1.2%
28.09	29	0.5%
27.62	5	0.1%
27.4	4	0.1%
27.39	21	0.3%

engine
Real number (ℝ)

High correlation

Distinct	126
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1426.3133

Minimum	624
Maximum	3604
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	624
5-th percentile	796
Q1	1197
median	1248
Q3	1498
95-th percentile	2499
Maximum	3604
Range	2980
Interquartile range (IQR)	301

Descriptive statistics

Standard deviation	484.68346
Coefficient of variation (CV)	0.33981557
Kurtosis	1.1282984
Mean	1426.3133
Median Absolute Deviation (MAD)	213
Skewness	1.2635795
Sum	8577848
Variance	234918.06
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1248	949	15.8%
1197	604	10.0%
796	360	6.0%
998	343	5.7%
1498	292	4.9%
2179	290	4.8%
1396	234	3.9%
1199	167	2.8%
2523	160	2.7%
1461	148	2.5%
Other values (116)	2467	41.0%

Value	Count	Frequency (%)
624	16	0.3%
793	5	0.1%
796	360	6.0%
799	61	1.0%
814	92	1.5%
909	2	< 0.1%
936	29	0.5%
993	24	0.4%
995	40	0.7%
998	343	5.7%

Value	Count	Frequency (%)
3604	1	< 0.1%
3498	1	< 0.1%
3198	2	< 0.1%
2999	2	< 0.1%
2997	2	< 0.1%
2993	12	0.2%
2987	8	0.1%
2982	23	0.4%
2967	8	0.1%
2956	14	0.2%

max_power
Real number (ℝ)

High correlation Zeros

Distinct	313
Distinct (%)	5.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	85.123178

Minimum	0
Maximum	400
Zeros	191
Zeros (%)	3.2%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	0
5-th percentile	37.48
Q1	67.05
median	81.8
Q3	99
95-th percentile	147.835
Maximum	400
Range	400
Interquartile range (IQR)	31.95

Descriptive statistics

Standard deviation	35.048717
Coefficient of variation (CV)	0.41174117
Kurtosis	4.4179195
Mean	85.123178
Median Absolute Deviation (MAD)	14.8
Skewness	1.0380631
Sum	511930.8
Variance	1228.4126
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
74	282	4.7%
0	191	3.2%
88.5	168	2.8%
67	138	2.3%
46.3	136	2.3%
81.8	120	2.0%
62.1	119	2.0%
67.1	119	2.0%
67.04	117	1.9%
70	113	1.9%
Other values (303)	4511	75.0%

Value	Count	Frequency (%)
0	191	3.2%
32.8	2	< 0.1%
34.2	18	0.3%
35	14	0.2%
35.5	2	< 0.1%
37	71	1.2%
37.48	8	0.1%
37.5	6	0.1%
38	1	< 0.1%
38.4	2	< 0.1%

Value	Count	Frequency (%)
400	1	< 0.1%
282	1	< 0.1%
280	1	< 0.1%
272	1	< 0.1%
270.9	3	< 0.1%
265	1	< 0.1%
261.4	4	0.1%
258	2	< 0.1%
254.8	3	< 0.1%
254.79	1	< 0.1%

seats
Real number (ℝ)

High correlation

Distinct	9
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.4238444

Minimum	2
Maximum	14
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	2
5-th percentile	5
Q1	5
median	5
Q3	5
95-th percentile	7
Maximum	14
Range	12
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.9789588
Coefficient of variation (CV)	0.18049168
Kurtosis	4.0881246
Mean	5.4238444
Median Absolute Deviation (MAD)	0
Skewness	2.0143169
Sum	32619
Variance	0.95836034
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
5	4762	79.2%
7	820	13.6%
8	196	3.3%
4	97	1.6%
9	69	1.1%
6	49	0.8%
10	18	0.3%
2	2	< 0.1%
14	1	< 0.1%

Value	Count	Frequency (%)
2	2	< 0.1%
4	97	1.6%
5	4762	79.2%
6	49	0.8%
7	820	13.6%
8	196	3.3%
9	69	1.1%
10	18	0.3%
14	1	< 0.1%

Value	Count	Frequency (%)
14	1	< 0.1%
10	18	0.3%
9	69	1.1%
8	196	3.3%
7	820	13.6%
6	49	0.8%
5	4762	79.2%
4	97	1.6%
2	2	< 0.1%

torque_Nm
Real number (ℝ)

High correlation Skewed Zeros

Distinct	226
Distinct (%)	3.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	162.55135

Minimum	0
Maximum	38038.7
Zeros	192
Zeros (%)	3.2%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	0
5-th percentile	12.5
Q1	90
median	145
Q3	200
95-th percentile	330
Maximum	38038.7
Range	38038.7
Interquartile range (IQR)	110

Descriptive statistics

Standard deviation	497.65903
Coefficient of variation (CV)	3.0615497
Kurtosis	5582.7085
Mean	162.55135
Median Absolute Deviation (MAD)	55
Skewness	73.347742
Sum	977583.8
Variance	247664.51
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
200	517	8.6%
190	483	8.0%
90	304	5.1%
114	196	3.3%
0	192	3.2%
113	154	2.6%
160	141	2.3%
62	139	2.3%
250	115	1.9%
69	111	1.8%
Other values (216)	3662	60.9%

Value	Count	Frequency (%)
0	192	3.2%
4.8	1	< 0.1%
5.7	1	< 0.1%
6.1	12	0.2%
7.8	5	0.1%
8.5	9	0.1%
8.6	6	0.1%
9.2	1	< 0.1%
9.8	9	0.1%
10.2	1	< 0.1%

Value	Count	Frequency (%)
38038.7	1	< 0.1%
789	3	< 0.1%
640	1	< 0.1%
620	6	0.1%
619	3	< 0.1%
600	3	< 0.1%
580	2	< 0.1%
560	2	< 0.1%
550	6	0.1%
540	1	< 0.1%

torque_rpm_min
Real number (ℝ)

High correlation Zeros

Distinct	62
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2474.6432

Minimum	0
Maximum	5000
Zeros	283
Zeros (%)	4.7%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	0
5-th percentile	200
Q1	1750
median	2000
Q3	3500
95-th percentile	4500
Maximum	5000
Range	5000
Interquartile range (IQR)	1750

Descriptive statistics

Standard deviation	1253.6837
Coefficient of variation (CV)	0.5066119
Kurtosis	-0.90316054
Mean	2474.6432
Median Absolute Deviation (MAD)	600
Skewness	0.13676535
Sum	14882504
Variance	1571722.8
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1750	865	14.4%
4000	691	11.5%
2000	650	10.8%
3500	589	9.8%
1500	319	5.3%
1400	284	4.7%
0	283	4.7%
1800	273	4.5%
3000	266	4.4%
2500	198	3.3%
Other values (52)	1596	26.5%

Value	Count	Frequency (%)
0	283	4.7%
21	1	< 0.1%
100	9	0.1%
175	1	< 0.1%
200	17	0.3%
250	1	< 0.1%
300	1	< 0.1%
400	4	0.1%
500	89	1.5%
600	6	0.1%

Value	Count	Frequency (%)
5000	20	0.3%
4850	19	0.3%
4800	73	1.2%
4750	7	0.1%
4700	7	0.1%
4600	49	0.8%
4500	159	2.6%
4400	55	0.9%
4388	1	< 0.1%
4386	60	1.0%

torque_rpm_max
Real number (ℝ)

High correlation Zeros

Distinct	58
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2815.6864

Minimum	0
Maximum	5300
Zeros	276
Zeros (%)	4.6%
Negative	0
Negative (%)	0.0%
Memory size	94.0 KiB

Quantile statistics

Minimum	0
5-th percentile	465
Q1	2000
median	2800
Q3	3750
95-th percentile	4500
Maximum	5300
Range	5300
Interquartile range (IQR)	1750

Descriptive statistics

Standard deviation	1151.1097
Coefficient of variation (CV)	0.40882028
Kurtosis	-0.0026671182
Mean	2815.6864
Median Absolute Deviation (MAD)	800
Skewness	-0.53267712
Sum	16933538
Variance	1325053.5
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4000	724	12.0%
2000	650	10.8%
3500	573	9.5%
3000	483	8.0%
1750	444	7.4%
2500	416	6.9%
2750	337	5.6%
2800	321	5.3%
0	276	4.6%
4200	189	3.1%
Other values (48)	1601	26.6%

Value	Count	Frequency (%)
0	276	4.6%
100	9	0.1%
200	11	0.2%
250	1	< 0.1%
300	1	< 0.1%
400	3	< 0.1%
500	100	1.7%
600	6	0.1%
700	28	0.5%
750	6	0.1%

Value	Count	Frequency (%)
5300	1	< 0.1%
5200	1	< 0.1%
5000	22	0.4%
4850	19	0.3%
4800	73	1.2%
4750	7	0.1%
4700	7	0.1%
4600	50	0.8%
4500	165	2.7%
4400	55	0.9%

	engine	fuel	km_driven	max_power	mileage	owner	seats	seller_type	selling_price	torque_Nm	torque_rpm_max	torque_rpm_min	transmission	year
engine	1.000	0.447	0.306	0.688	-0.430	0.076	0.526	0.099	0.465	0.657	-0.343	-0.553	0.400	-0.040
fuel	0.447	1.000	0.036	0.145	0.290	0.024	0.214	0.047	0.101	0.000	0.453	0.532	0.035	0.134
km_driven	0.306	0.036	1.000	0.014	-0.199	0.033	0.194	0.000	-0.294	0.074	-0.363	-0.349	0.016	-0.573
max_power	0.688	0.145	0.014	1.000	-0.287	0.101	0.315	0.160	0.644	0.711	0.069	-0.191	0.513	0.225
mileage	-0.430	0.290	-0.199	-0.287	1.000	0.095	-0.435	0.039	0.028	-0.033	-0.082	0.150	0.249	0.349
owner	0.076	0.024	0.033	0.101	0.095	1.000	0.021	0.132	0.363	0.037	0.123	0.138	0.118	0.259
seats	0.526	0.214	0.194	0.315	-0.435	0.021	1.000	0.022	0.320	0.375	-0.123	-0.366	0.033	0.050
seller_type	0.099	0.047	0.000	0.160	0.039	0.132	0.022	1.000	0.161	0.000	0.071	0.099	0.217	0.103
selling_price	0.465	0.101	-0.294	0.644	0.028	0.363	0.320	0.161	1.000	0.649	0.035	-0.162	0.465	0.705
torque_Nm	0.657	0.000	0.074	0.711	-0.033	0.037	0.375	0.000	0.649	1.000	-0.188	-0.309	0.014	0.307
torque_rpm_max	-0.343	0.453	-0.363	0.069	-0.082	0.123	-0.123	0.071	0.035	-0.188	1.000	0.766	0.127	0.243
torque_rpm_min	-0.553	0.532	-0.349	-0.191	0.150	0.138	-0.366	0.099	-0.162	-0.309	0.766	1.000	0.131	0.163
transmission	0.400	0.035	0.016	0.513	0.249	0.118	0.033	0.217	0.465	0.014	0.127	0.131	1.000	0.153
year	-0.040	0.134	-0.573	0.225	0.349	0.259	0.050	0.103	0.705	0.307	0.243	0.163	0.153	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

	name	year	selling_price	km_driven	fuel	seller_type	transmission	owner	mileage	engine	max_power	seats	torque_Nm	torque_rpm_min	torque_rpm_max
0	Maruti Swift Dzire VDI	2014	450000	145500	Diesel	Individual	Manual	First Owner	23.40	1248.0	74.00	5.0	190.0	2000.0	2000.0
1	Skoda Rapid 1.5 TDI Ambition	2014	370000	120000	Diesel	Individual	Manual	Second Owner	21.14	1498.0	103.52	5.0	250.0	1500.0	2500.0
2	Hyundai i20 Sportz Diesel	2010	225000	127000	Diesel	Individual	Manual	First Owner	23.00	1396.0	90.00	5.0	22.4	1750.0	2750.0
3	Maruti Swift VXI BSIII	2007	130000	120000	Petrol	Individual	Manual	First Owner	16.10	1298.0	88.20	5.0	11.5	500.0	500.0
4	Hyundai Xcent 1.2 VTVT E Plus	2017	440000	45000	Petrol	Individual	Manual	First Owner	20.14	1197.0	81.86	5.0	113.7	4000.0	4000.0
5	Maruti Wagon R LXI DUO BSIII	2007	96000	175000	LPG	Individual	Manual	First Owner	17.30	1061.0	57.50	5.0	7.8	500.0	500.0
6	Maruti 800 DX BSII	2001	45000	5000	Petrol	Individual	Manual	Second Owner	16.10	796.0	37.00	4.0	59.0	2500.0	2500.0
7	Toyota Etios VXD	2011	350000	90000	Diesel	Individual	Manual	First Owner	23.59	1364.0	67.10	5.0	170.0	1800.0	2400.0
8	Ford Figo Diesel Celebration Edition	2013	200000	169000	Diesel	Individual	Manual	First Owner	20.00	1399.0	68.10	5.0	160.0	2000.0	2000.0
9	Renault Duster 110PS Diesel RxL	2014	500000	68000	Diesel	Individual	Manual	Second Owner	19.01	1461.0	108.45	5.0	248.0	2250.0	2250.0

	name	year	selling_price	km_driven	fuel	seller_type	transmission	owner	mileage	engine	max_power	seats	torque_Nm	torque_rpm_min	torque_rpm_max
6986	Maruti Alto LXi	2011	200000	73000	Petrol	Individual	Manual	First Owner	19.70	796.0	46.30	5.0	62.0	3000.0	3000.0
6987	Maruti 800 AC	1997	40000	120000	Petrol	Individual	Manual	First Owner	16.10	796.0	37.00	4.0	59.0	2500.0	2500.0
6988	Maruti Alto K10 VXI Airbag	2017	340000	45000	Petrol	Individual	Manual	First Owner	23.95	998.0	67.10	5.0	90.0	3500.0	3500.0
6990	Hyundai i20 Magna	2013	380000	25000	Petrol	Individual	Manual	First Owner	18.50	1197.0	82.85	5.0	113.7	4000.0	4000.0
6991	Maruti Wagon R LXI Optional	2017	360000	80000	Petrol	Individual	Manual	First Owner	20.51	998.0	67.04	5.0	90.0	3500.0	3500.0
6992	Hyundai Santro Xing GLS	2008	120000	191000	Petrol	Individual	Manual	First Owner	17.92	1086.0	62.10	5.0	96.1	3000.0	3000.0
6993	Maruti Wagon R VXI BS IV with ABS	2013	260000	50000	Petrol	Individual	Manual	Second Owner	18.90	998.0	67.10	5.0	90.0	3500.0	3500.0
6994	Hyundai i20 Magna	2013	320000	110000	Petrol	Individual	Manual	First Owner	18.50	1197.0	82.85	5.0	113.7	4000.0	4000.0
6995	Hyundai Verna CRDi SX	2007	135000	119000	Diesel	Individual	Manual	Fourth & Above Owner	16.80	1493.0	110.00	5.0	24.0	750.0	900.0
6996	Maruti Swift Dzire ZDi	2009	382000	120000	Diesel	Individual	Manual	First Owner	19.30	1248.0	73.90	5.0	190.0	2000.0	2000.0

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Interactions

Correlations

Missing values

Sample